(a) Field of the Invention
The field of invention is optimization and management of a serial, non-linear, hydropower generation system on an hourly basis based on economic and trader inputs. The optimization and management system described herein uses a global linearization approach and mixed integer linear programming to perform the dispatch and to schedule a river system for ten days forward while subject to real world, hourly physical, biological, environmental, and recreation constraints.
(b) Description of Related Art
In many areas of the country, watershed systems are managed by systems comprising a series of hydroelectric dams that provide significant electrical power to the surrounding area. These hydroelectric systems are very complex, and past and present management tools are inadequate to accommodate the variables, constraints, and other complexities of these systems.
For example, power in the northwest United States comes from a variety of sources and levels. The largest provider of hydropower in the northwest United States is the Columbia watershed system. Other power generation sources include natural gas, turbine engines, wind, and solar power. Because the Columbia River 8 watershed provides an abundant source of hydroelectric power, the cost to produce this power is much less than other power resources. Consequently, the administrative authority, Bonneville Power Administration (“BPA”), wields considerable influence over the local power market.
The Columbia River watershed consists of a series of forty-two dams along the main rivers and tributaries. Not all of the dams have power generation capacity. Further, those dams which do have power generation capacity do not run all at the same time. The Columbia River 8 watershed system was initially built for flood control, irrigation, navigation, recreation, fishing, and lastly hydroelectric power.
The design purposes of the Columbia River watershed system represent varying levels of competing interests for use of the natural resource. These competing interests include the local farming communities that require flood control and irrigation, the nautical transportation industry that requires a minimum flow to maintain a navigable waterway, and the fishing and recreational communities that use the waterway in various ways. These competing interests limit the BPA's ability to maximize the hydroelectric power capacity of the Columbia River watershed system. Consequently much of the storage capacity may go unused.
Within the geographic region served by BPA are a series of municipalities, counties, and public utility districts (PUD's), which are essentially areas comprising an aggregate group of power users. Each municipality, county, or public utility district may have varying load requirements based on its own unique demographic characteristics. For example, one PUD may be comprised of industrial type power users, while another PUD may be comprised of residential communities. Thus the power load required to service these users varies based on characteristics such as time and quantity of use. BPA distributes the power to the respective power users including PUD's. These power users generally in turn sell the power to the consumer such as businesses and residences. The power may also be traded on the open market.
To alleviate the high overhead of managing such a complex power distribution and accounting system, the BPA developed an “energy product” to sell to the various PUD's. The sale of this energy product is based on an entitlement system called the “Slice” entitlement system. The energy product is itself referred to as a “Slice contract.” Each qualified PUD has the option of entering into a long term Slice contract entitling the PUD to a certain percentage of the hydroelectric power output from the BPA over a given period of time. PUDs that do so are called “Slice customers.” In many instances, the Slice contract is but one of many power resources that might comprise a PUD's energy sources.
The Slice product itself is predominantly comprised of hydropower generation resources. Like other hydropower resources, it is unique in that the present use of the resource influences how much of the resource is available in the future. For example, once water is released from a reservoir to generate electricity, that water is not immediately replaced. Nature replaces the resource through precipitation and runoff. Therefore, effective planning and forecasting of the Slice resource is essential to the Slice customer's long-term profitability.
The Slice resource consists of two main components—a “Balance-of-System” (“BOS”) component and a “Dispatchable” Slice component. The BOS consists of non-hydropower generation, primarily generation from the Columbia Generation Station Nuclear Reactor, and hydropower generation from the Snake River. The BOS generation is non-dispatchable meaning that the amount of BOS generation in each hour is determined by BPA and communicated to the customer.
Approaches to Managing the Contract
There are potentially a number of approaches available to Slice customers in deciding how to manage their Slice resource. Broadly speaking, there are two different types of approach, each of which has several varieties. The first type is a “shaping and validation” approach. The second type is optimization.
A. Shaping and Validation
The shaping and validation approaches rely on the fact that BPA has provided a system that will take the schedules as submitted by a customer and, in a sequential order, apply the various constraints to those schedules. If the schedules are outside the constraints for a specific dam for a specific hour the system, a computer program known as a simulator and operated by BPA, will attempt to modify those schedules to bring them into compliance. Therefore, utilities taking this approach will attempt to create schedules that are reasonably close to meeting the constraints, and then have the simulator modify them to bring them within compliance.
B. Operator Driven Management
The approach that BPA uses to run the actual Columbia River system is to allow planners and operators to use their own judgment and tools to manage the system and keep the system within the constraints. BPA has arrived at a number of heuristics to enable this approach, such heuristics including keeping the lower Columbia River projects between one-half and two-thirds full for example. A Slice customer pursuing this option will generate the schedules suggested by the heuristics and then let BPA's simulator determine how the schedules need to be modified to make them feasible.
C. Statistical Simulation
Another simulator-based approach is to algorithmically generate many potential schedules which would all be run through the customer's own version of Simulator so that the Simulator could determine which ones of those are feasible.
D. Basic Shaping
A third approach is to develop a tool to generate a reasonable schedule based on one of a set of possible strategies. An example of a strategy would be to gradually fill or draft Grand Coulee and then, within those confines, to put more generation into peak hours (7 am to 10 pm) and less in the other hours. This schedule would then be submitted to the simulator to be turned into a feasible schedule.
E. Other Optimization Approaches
The other type of approach to managing the Slice contract is to reach an optimization by solving the hydropower and generation variables subject to the constraint equations. Given that the variables have non-linear relationships to one another, there are a few different strategies that may be employ to accomplish this optimization.
E.1. Non-Linear Solver
Given that the problem is non-linear, one approach is to use a non-linear solver to solve the system.
E.2. Successive Linear Approximation
Another approach is to use the successive linear approximation (SLA) technique. In this technique, one posits an initial solution and linearizes the equations around this solution via first order Taylor series approximations, and then seek a better solution in the region around one's initial solution. This procedure is repeated until convergence is reached.
E.3 Stochastic Optimization
Yet another approach is to recognize the fact that while the problem that BPA presents is a deterministic problem—i.e. the inputs to the system such as the inflow forecasts and the constraints are presumed to be correct and must be honored by the customer's schedules—that in reality those inputs will change in unpredictable ways prior to the time when they become realized. The problem therefore is fundamentally random and to solve it while recognizing that randomness is best done using a stochastic optimization approach.
Insufficiency of Past and Current Approaches
Given complexities of the competing interest and non-linearity of optimizing power generation from the multi-dam hydropower generation system, none of the approaches listed above deliver a reasonable chance of delivering an adequate optimization in a timely manner. The primary impediment is the need to dispatch the river rapidly enough given the time constraints of the 45-minute window faced by the traders, as explained below.
Using any of the optimization techniques mentioned above would mean the process to produce feasible schedules would be too long to run on an hourly basis. Therefore the traders would need to dispatch the system for multiple hours or a day at a time. This approach would compromise ability to flexibly change the generation and capacity on an hourly basis, which was the main reason for becoming a Slice customer in the first place.
The nature of the shaping and validation approaches places substantial limitations on the ability to accurately shape the schedules on an hourly basis or in real-time. Faced with these limitations, the traders are forced to propose schedules further in advance. The necessity of this extra lead time means that the trader can still propose a schedule, but without any assurance that the request will be accepted by the management authority. Without these assurances, the trader typically chooses a more conservative scheduling request, seeking a schedule in the middle of the range of possible values in order to have the highest chance of receiving what is requested.
The present system and method seeks to address the complexities and limitations explained above by providing an optimization and management system that uses a global linearization approach and mixed integer linear programming to perform the dispatch and to schedule a multi-dam hydropower system for an allotted look-ahead time period while subject to real world, hourly physical, biological, environmental, and recreational constraints.